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As matrix method for Hamiltonian class #241

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Jun 7, 2023
Merged

As matrix method for Hamiltonian class #241

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409ac97
added as_matrix method for Hamiltonian class
AlexisRalli May 28, 2023
5960e23
added check for if number of qubits is above 20
AlexisRalli May 28, 2023
0d48ef7
added unittest for as_matrix method
AlexisRalli May 28, 2023
a3edfc0
refactored code and added code comments
AlexisRalli Jun 1, 2023
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45 changes: 45 additions & 0 deletions src/openqaoa-core/qaoa_components/ansatz_constructor/operators.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,9 @@
from typing import List, Union, Tuple
from sympy import Symbol
import numpy as np
from scipy.sparse import kron as sparse_kron
from functools import reduce
from scipy.sparse import csr_matrix

Identity = np.array(([1, 0], [0, 1]), dtype=complex)
PauliX = np.array(([0, 1], [1, 0]), dtype=complex)
Expand Down Expand Up @@ -686,3 +689,45 @@ def classical_hamiltonian(
raise ValueError("Hamiltonian only supports Linear and Quadratic terms")

return cls(pauli_ops, pauli_coeffs, constant)

@property
def as_matrix(self):
"""
Build sparse matrix of Hamiltonian. Note this includes self.constant value.

Returns
-------
H_mat:
sparse matrix of Hamiltonian.
"""

if self.n_qubits>20:
raise ValueError('number of qubits exceeds maximum of 20')

p_mat_dict = {'X': csr_matrix([[0, 1],
[1, 0]]),
'Y': csr_matrix([[0., -1j],
[1j, 0.]]),
'Z': csr_matrix([[1, 0],
[0, -1]]),
'I': csr_matrix([[1, 0], [0, 1]])}

converter = lambda s: p_mat_dict[s]

# vectorized function to map single qubit pauli strings to sparse matrix
vfunc = np.vectorize(converter)

base = np.array(['I' for _ in range(self.n_qubits)])

H_mat = reduce(sparse_kron, vfunc(base)) * self.constant
for P, coeff in zip(self.terms, self.coeffs):
temp = base.copy()

# replace single qubit pauli I in base term
# with single qubit pauli operators according to qubit_indices and pauli_strs in P
temp[np.array(P.qubit_indices)] = np.array(list(P.pauli_str))

# take kronecker product of sparse list of matrices
H_mat += reduce(sparse_kron, vfunc(temp)) * coeff

return H_mat
68 changes: 68 additions & 0 deletions tests/test_operators.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1314,6 +1314,74 @@ def test_hamiltonian_dict(self):
hamiltonian_dict_pauliop == correct_dict_pauliop
), "Hamiltonian dictionary did not yield correct dictionary"

def test_hamiltonian_as_matrix(self):
"""Test if the method produces
the correct matrix corresponding to given Hamiltonian.

"""
P_list = ['XIIZ', 'YIII', 'IZXI', 'IXIY', 'IIIZ', 'IIXI', 'ZZII']
coeff_list = list(range(1, 8))

Pauli_list = []
for P in P_list:
P = np.array(list(P))
non_I = np.where(P != 'I')[0]
Pauli_list.append(PauliOp(P[non_I], tuple(non_I)))

H = Hamiltonian(Pauli_list, coeff_list, 0)

solution = np.array([[12. + 0.j, 0. + 0.j, 9. + 0.j, 0. + 0.j, 0. + 0.j, 0. - 4.j,
0. + 0.j, 0. + 0.j, 1. - 2.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j],
[0. + 0.j, 2. + 0.j, 0. + 0.j, 9. + 0.j, 0. + 4.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 0. + 0.j, -1. - 2.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j],
[9. + 0.j, 0. + 0.j, 12. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, 0. - 4.j, 0. + 0.j, 0. + 0.j, 1. - 2.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j],
[0. + 0.j, 9. + 0.j, 0. + 0.j, 2. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 4.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, -1. - 2.j,
0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j],
[0. + 0.j, 0. - 4.j, 0. + 0.j, 0. + 0.j, -2. + 0.j, 0. + 0.j,
3. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
1. - 2.j, 0. + 0.j, 0. + 0.j, 0. + 0.j],
[0. + 4.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, -12. + 0.j,
0. + 0.j, 3. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, -1. - 2.j, 0. + 0.j, 0. + 0.j],
[0. + 0.j, 0. + 0.j, 0. + 0.j, 0. - 4.j, 3. + 0.j, 0. + 0.j,
-2. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 1. - 2.j, 0. + 0.j],
[0. + 0.j, 0. + 0.j, 0. + 4.j, 0. + 0.j, 0. + 0.j, 3. + 0.j,
0. + 0.j, -12. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 0. + 0.j, -1. - 2.j],
[1. + 2.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, -2. + 0.j, 0. + 0.j, 9. + 0.j, 0. + 0.j,
0. + 0.j, 0. - 4.j, 0. + 0.j, 0. + 0.j],
[0. + 0.j, -1. + 2.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 0. + 0.j, -12. + 0.j, 0. + 0.j, 9. + 0.j,
0. + 4.j, 0. + 0.j, 0. + 0.j, 0. + 0.j],
[0. + 0.j, 0. + 0.j, 1. + 2.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 9. + 0.j, 0. + 0.j, -2. + 0.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 0. + 0.j, 0. - 4.j],
[0. + 0.j, 0. + 0.j, 0. + 0.j, -1. + 2.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 0. + 0.j, 9. + 0.j, 0. + 0.j, -12. + 0.j,
0. + 0.j, 0. + 0.j, 0. + 4.j, 0. + 0.j],
[0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 1. + 2.j, 0. + 0.j,
0. + 0.j, 0. + 0.j, 0. + 0.j, 0. - 4.j, 0. + 0.j, 0. + 0.j,
12. + 0.j, 0. + 0.j, 3. + 0.j, 0. + 0.j],
[0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, -1. + 2.j,
0. + 0.j, 0. + 0.j, 0. + 4.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, 2. + 0.j, 0. + 0.j, 3. + 0.j],
[0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
1. + 2.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. - 4.j,
3. + 0.j, 0. + 0.j, 12. + 0.j, 0. + 0.j],
[0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j, 0. + 0.j,
0. + 0.j, -1. + 2.j, 0. + 0.j, 0. + 0.j, 0. + 4.j, 0. + 0.j,
0. + 0.j, 3. + 0.j, 0. + 0.j, 2. + 0.j]])

assert np.allclose(solution,
H.as_matrix.toarray()), 'as_matrix method not correct'


if __name__ == "__main__":
unittest.main()